Exploratory Analysis of Variables and Creating Robust Regression Model or Geodemographic Classificat

Part 1: Exploratory Analysis of Variables

Part 1 Conduct an exploratory analysis of the variables listed in Table 1, from the 2011_OAC_Raw_uVariables-GY7702_2021-22_CW2.csv dataset, for the OAs in the LAD assigned to you in the table in the Appendix.Include the code, the output (can include graphics) and a description of the findings. The latter should beup to 500 words and it can be written as a final discussion after the analysis, or as adescription of each stepof the analysis, or a combination of the two.Table 1: Variables to be used for Part 1 and 2 of this assignment.VariableCode VariableDescription Part 2 Chose and answer to ONLY ONE of the two options available below (2.A or 2.B). Option 2.A Use the variables explored in Part 1 (see Table 1) to create a robust (where possible), multiple linearregression model. The model should have as outcome (dependent) variable an indicator of the health of the population (per OA in the LAD assigned to you in the table in the Appendix). The indicator can be one of the variables explored in Part 1 (see Table 1) or a combination thereof. The model should have as predictors (independent) variables a relevant set of variables related to education and occupation. health = (education + occupation) + erro Present the model that achieves the best fit and the process through which it has been identified. Include the code, the output (can include graphics), a discussion of the process and an interpretation of the final model. The latter two should be up to 500 words and it can be written as a final discussion after the analysis, or as a description of each step of the analysis, or a combination of the two. Alternatively, if no robust model or no significant model can be created for the LAD assigned to you, include the code and the output (can include graphics) that illustrate that finding, and a related discussion (still, up to 500 words). The latter could be written as a final discussion after the analysis, or as a description of each step of the analysis, or a combination of the two. Option 2.B Create a geodemographic classification for the OAs in the LAD assigned to you in the table in the Appendix, using the variables explored in Part 1 (see Table 1). Include the code, the output (can include graphics) and a discussion of the classification. The latter should be up to 500 words and it can be written as a final discussion after the analysis, or as a description of each step of the analysis, or a combination of the two. Part 3 Write a brief discussion (maximum 200 words, excluding references) of the approach taken to create the submitted document and its level of reproducibility. Note: if you create a repository for this project, you must create an anonymous-looking username (e.g., signing up with your university email if you are already otherwise registered on GitHub or GitLab) to create a repository. The repository MUST BE PRIVATE. Add the module convener as a collaborator – sdesabbata on GitHub, please check with the module convener if you use another platform. Include the full, plain URL (e.g., https://github.com/sdesabbata/r-for-geographic-data-science) in your submission, as links tend not to work properly on TurnItIn. Note: include a paragraph such as the one below to comply with the Open Government licence and the other data licences, both in your final document and in the repository’s README.md file (if you create one)